Senior AI/ML Engineer

This is a fully remote position, open to applicants in Nevada.

📋 Description

• Develop and deliver AI/ML functionalities across various stages including data preparation, training or fine-tuning, evaluation, deployment, and monitoring.

• Take ownership of features from inception to completion and refine them based on feedback from production.

• Create RAG pipelines and engage with LLM APIs and open-source models.

• Design reliable prompts and contribute to agentic workflows.

• Construct data pipelines, labeling workflows, and evaluation frameworks.

• Implement AI solutions in manufacturing and supply chain operations, including applications in computer vision for quality inspection, predictive maintenance, sensor data analysis, demand forecasting, inventory planning, supplier risk assessment, and logistics.

• Collaborate with teams in Vehicle Engineering, Manufacturing, and Operations to convert requirements into quantifiable AI systems.

• Write code, conduct experiments, and deploy production systems.

• Work directly with stakeholders to develop products independently of a product manager.

• Report directly to the Distinguished Engineer of Generative AI.

⛳️ Requirements

• A Bachelor’s degree is required.

• A PhD in a relevant discipline is a strong asset for early-career applicants.

• Candidates lacking a PhD should possess 3+ years of professional or research experience focused on ML systems.

• A solid foundational understanding of ML concepts, including model training, loss functions, evaluation metrics, overfitting, and regularization.

• Practical experience in supervised learning, NLP, computer vision, and time-series modeling.

• Familiarity with LLM APIs such as OpenAI, Anthropic, Gemini, or similar platforms.

• Basic knowledge of RAG, embeddings, or retrieval systems.

• Capability to rigorously evaluate model quality.

• Proficiency in Python with experience in PyTorch or JAX, Hugging Face, pandas, and scikit-learn.

• Ability to produce production-quality code.

• Familiarity with cloud platforms such as AWS, GCP, or Azure.

• Experience with version control, experiment tracking, and fundamental MLOps practices.

• A background or genuine interest in Mechanical Engineering, Electrical Engineering, Robotics, Industrial Engineering, or a related physical discipline is appreciated.

• Exposure to computer vision, sensor data, or real-time systems is a plus.

• Familiarity with supply chain, logistics, or operations research challenges is valued.

• Experience with simulation environments or physical hardware in a research or lab context is beneficial.

• An MS or PhD in a related field is preferred.

• Ability to work collaboratively across disciplines and articulate technical decisions to non-technical stakeholders.

🏝️ Benefits

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Life insurance.

• Disability insurance.

• Vacation.

• 401k.

• Eligibility for an equity program.

• Eligibility for a discretionary annual incentive program.